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Power optimization method of direct drive wave energy converter based on model improvement
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Shuiyuan Li, Junhua Yang, Cunjie Deng, Zhihao Zeng, Yaya Feng, Junhui Wei
Renewable Energy Resources | 2025, 43(12) : 1697 - 1704
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Renewable Energy Resources | 2025, 43(12): 1697-1704
Power optimization method of direct drive wave energy converter based on model improvement
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Shuiyuan Li, Junhua Yang, Cunjie Deng, Zhihao Zeng, Yaya Feng, Junhui Wei
Affiliations
  • School of Automation, Guangdong University of Technology, Guangzhou 510006, China
Published: 2025-12-20
Outline
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To address the issue of low wave energy capture efficiency caused by the nonlinear effects in the actual operating conditions of wave energy conversion devices, a model-based improved power optimization strategy is proposed. Considering the resultant force acting on the free state of the float, an equivalent approximation is carried out using series expansion, and an independent iterative algorithm is introduced. Based on the Kalman filter with statistical similarity measurement, the polynomial coefficients are determined, and then the Euler-Lagrange equations are established to obtain the optimal control law. By tracking the control current, the maximum power can be captured. Simulation results show that the improved Kalman filter can reduce the influence of noise and the parameter identification error. The proposed strategy can effectively enhance the output power of the system under actual operating conditions.

model improvement  /  optimal control  /  statistical similarity measurement  /  power optimization  /  parameter identification
黎水源, 杨俊华, 邓存杰, 曾智好, 冯娅娅, 魏俊辉. 基于模型改进的直驱式波浪能转换装置功率优化策略. 可再生能源, 2025 , 43 (12) : 1697 -1704 .
Shuiyuan Li, Junhua Yang, Cunjie Deng, Zhihao Zeng, Yaya Feng, Junhui Wei. Power optimization method of direct drive wave energy converter based on model improvement[J]. Renewable Energy Resources, 2025 , 43 (12) : 1697 -1704 .
Year 2025 volume 43 Issue 12
89
25
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  • Receive Date:2025-03-25
  • Online Date:2026-09-23
  • Published:2025-12-20
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  • Received:2025-03-25
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    School of Automation, Guangdong University of Technology, Guangzhou 510006, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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